Ubiquitous naturally occurring autoantibodies (nAbs) against alpha-synuclein (α-syn) may play important roles in the pathogenesis of Multiple System Atrophy (MSA) and Parkinson's disease (PD). Recently, we reported reduced high-affinity/avidity anti-α-syn nAbs levels in plasma from MSA and PD patients, along with distinct inter-group immunoglobulin (Ig)G subclass distributions. The extent to which these observations in plasma may reflect corresponding levels in the cerebrospinal fluid (CSF) is unknown.
Using competitive and indirect ELISAs, we investigated the affinity/avidity of CSF anti-α-syn nAbs as well as the CSF and plasma distribution of IgG subclasses and IgM nAbs in a cross-sectional cohort of MSA and PD patients.
Repertoires of high-affinity/avidity anti-α-syn IgG nAbs were reduced in CSF samples from MSA and PD patients compared to controls. Furthermore, anti-α-syn IgM nAb levels were relatively lower in CSF and plasma from MSA patients but were reduced only in plasma from PD patients. Intereogical responses may reflect their specific disease pathophysiologies. These results are encouraging for further investigation of these immunological mechanisms in neurodegenerative diseases.Gait impairments are common in Parkinson's Disease (PD) and are likely caused by degeneration in multiple brain circuits, including the basal ganglia, thalamus and mesencephalic locomotion centers (MLC). Diffusion tensor imaging (DTI) assesses fractional anisotropy (FA) and mean diffusivity (MD) that reflect the integrity of neuronal microstructure. We hypothesized that DTI changes in motor circuits correlate with gait changes in PD.
We aimed to identify microstructural changes of brain locomotion control centers in PD via DTI and their correlations with clinical and quantitative measures of gait.
Twenty-one PD patients reporting gait impairment and 15 controls were recruited. Quantitative gait and clinical tests were recorded in PD subjects' medication ON and OFF states. Region of Interest (ROI) analysis of the thalamus, basal ganglia and MLC was performed using ExploreDTI. Correlations between FA/MD with clinical gait parameters were examined.
Microstructural changes were seen in the thalamus, caudah as gait, and potentially could serve as an imaging marker.Management of motor symptoms in Parkinson's Disease(PD) relies on subjective information provided by patients, the quality of which can be affected by many factors.
Objective data collected during daily life could complement this information and improve management of motor symptoms.
To assess the usefulness of the Personal KinetiGraph (PKG) in characterizing the intensity and timing of motor symptoms in PD patients.
Retrospective study of all PD patients followed at a tertiary academic movement disorders center assessed by PKG between December 1, 2016 and October 30, 2018. PKG was worn for 7 days prior to the clinical visit. We compared the information obtained from the interview and the clinical visit, and assessed the impact of the PKG on treatment decision making.
170 PKG results were reviewed. PKG complemented patient input in 82.9%(141/170) and led to medication changes in 71%(100/141) of the complemented inputs. PKG contributed the least to correcting or complementing patients' input when patients self-reported as undertreated (22%) and the most when patient were unable to answer all questions regarding motor response to individual doses (100%) (Fisher, p&lt;0.0001). The majority of patient undergoing 3 or 4 PKG encounters did not reach a controlled state as defined by PKG until the 3rd or 4th encounter, suggesting that repeated use of the PKG might be needed to help optimize motor control as therapy changes done after one encounter might not be enough.
PKG might be useful in supplementing patient-provided information for accurate assessment and treatment plan.
PKG might be useful in supplementing patient-provided information for accurate assessment and treatment plan.Particulate radioactivity, a characteristic of particulate matter, is primarily determined by the abundance of radionuclides that are bound to airborne particulates. Exposure to high levels of particulate radioactivity has been associated with negative health outcomes. However, there are currently no spatially and temporally resolved particulate radioactivity data for exposure assessment purposes. We estimated the monthly distributions of gross beta particulate radioactivity across the contiguous United States from 2001 to 2017 with a spatial resolution of 32 km, via a multi-stage ensemble-based model. https://www.selleckchem.com/products/etc-159.html Particulate radioactivity was measured at 129 RadNet monitors across the contiguous U.S. In stage one, we built 264 base learning models using six methods, then selected nine base models that provide different predictions. In stage two, we used a non-negative geographically and temporally weighted regression method to aggregate the selected base learner predictions based on their local performance. The results of block cross-validation analysis suggested that the non-negative geographically and temporally weighted regression ensemble learning model outperformed all base learning model with the smallest rooted mean square error (0.094 mBq/m3). Our model provided an accurate estimation of particulate radioactivity, thus can be used in future health studies.Daily exposure to air pollution has been shown to increase cardiovascular and respiratory mortality. While increases in short-term exposure to air pollutants at any daily concentrations has been shown to be associated to adverse health outcomes, days with extreme levels, also known as air pollution peaks based on specific thresholds, have been used to implement air quality alerts in various cities across the globe.
We aimed at evaluating the potential effects of the Air Quality Alerts (AQA) system on different causes of premature mortality in Paris, France.
Air quality alerts (AQA) based on particulate matter (PM) levels and related interventions were implemented in the region of Paris in 2008 and were revised to be more stringent in 2011. In this study, we applied a difference-in-differences (DID) approach coupled with propensity-score matching (PSM) to daily mortality data for the period 2000 to 2015 to evaluate the effects of the Paris AQA program on different causes of premature mortality for the entire population and for adults&gt;75years old.